Background: The highest concentrations of
blood glucose during the day are usually found
postprandialy. Postprandial hyperglycemia (PPH)
is likely to promote or aggravate fasting
hyperglycemia. Evidence in recent years suggests
that PPH may play an important role in functional
& structural disturbances in different body organs
particularly the cardiovascular system.
Objective: To evaluate the effect of (PPH) as a
risk factor for coronary Heart disease in Type 2
diabetic patients.
Methods: Sixty-three type2 diabetic patients
were included in this study. All have controlled
fasting blood glucose, with HbA1c correlation.
They were all followed for five months period
(from May to October 2008). A two hour
postprandial glucose (PPG) was done for all. Other
risk factors were taken in consideration such as
hypertension, obesity, and dyslipidemia. The study
was performed on those patients after at least three
months of controlled fasting blood glucose. ECG
was done to all of them.
Results : Out of the 63 type 2 diabetic patients,
20 had normal PPG and HbA1c levels, one of them
(5%), has ischemic changes on ECG twenty
patients had normal HbA1c & High PPG with 7
(35%) of them showed ischemic changes on ECG
17 patients showed a high PPG and a high HbA1c
with four of them showed ischemic changes on
ECG P<0.05. The remaining 6 patients had normal
PPG but high HbA1c & also only one of them
showed ischemic changes on ECG.
Conclusion This study showed that PPH is a
significant risk factor for ischemic heart disease
(IHD).
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Unlike welding, soldering does not involve melting the work pieces. Soldering is a process in which two or more items are joined together by melting and putting a filler metal (solder) into the joint. Failure in the solder joint may make the system components lose their functions. Electrical wiring and electronic components are joined to devices and printed circuit boards using soldering. Soldering and brazing are both used in the assembly of musical instruments. Lead-tin alloy solder employed in the current investigation which has a diameter of 4 mm and a density of 11.0103 kg/m3 with continuous heat flux heating from the domain's left side and complete insulation on the other side. The melting of PCM was simulated using the ANSYS
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In this article, a new deterministic primality test for Mersenne primes is presented. It also includes a comparative study between well-known primality tests in order to identify the best test. Moreover, new modifications are suggested in order to eliminate pseudoprimes. The study covers random primes such as Mersenne primes and Proth primes. Finally, these tests are arranged from the best to the worst according to strength, speed, and effectiveness based on the results obtained through programs prepared and operated by Mathematica, and the results are presented through tables and graphs.
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Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.
We compare two methods Bayesian and . Then the results were compared using MSe criteria.
A simulation had been used to study the empirical behavior for the Logistic model , with different sample sizes and variances. The results using represent that the Bayesian method is better than the at small samples sizes.
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The study aimed to recommend a new spectrophotometric-kinetic method for determination of carbamazepine (CABZ) in its pure form and pharmaceutical forms. The proposed procedure based on the coupling of CABZ with diazotized sulfanilic acid in basic medium to yield a colored azo dye. Factors affecting the reaction yield were studied and the conditions were optimized. The colored product was followed spectrophotometrically via monitoring its absorbance at 396 nm. Under the optimized conditions, two method (the initial rate and fixed time (10 minute)) were applied for constructing the calibration graphs. The graphs were linear in concentration ranges 2.0 to 18.0 µg.mL-1 for both methods. The proposed was applied successfully in
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Multiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of
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